Probabilistic Precipitation Forecast in (Indonesia) Using NMME Models: Case Study on Dry Climate Region
- 128 Downloads
Reliable precipitation forecast is one of the key inputs to generate accurate and reliable hydrological forecast. This paper uses the North American Multimodel Ensemble (NMME) models to generate seasonal precipitation forecasts in Indonesia. The NMME models are verified against observed precipitation, and the analysis shows that they are biased and underdispersive. The Bayesian Model Averaging (BMA) approach was applied to calibrate the forecast for reliable prediction. East Nusa Tenggara (NTT) is chosen as the pilot study since the region has been well recognized as a dry region with the highest degree of vulnerability toward drought. The results show that the BMA improves the forecast reliability. Moreover, the Canadian Meteorological Center (CMC) models outperform the others. The map of the forecasted Standardized Precipitation Index (SPI) is validated with the observation and shows a high prediction accuracy.
KeywordsCalibration Drought Hydrology NMME Underdispersive
- 2.Demargne, J., Brown, J.D., Liu, Y., Seo, D.-J., Wu, L., Toth, Z., Zhu, Y.: Diagnostic verification of hydrometeorological and hydrologic ensembles. Atmos. Sci. Lett. 11 (2010)Google Scholar
- 5.Setiawan, M., Koesmaryono, Y., Faqih, A., Gunawan, D.: North American multi model ensemble (NMME) performance of monthly precipitation forecast over south Sulawesi, Indonesia. IOP Conf. Ser.: Earth Environ. Sci. 58, 012035 (2017)Google Scholar
- 6.Becker, E., van den Dool, H., Zhang, Q.: Predictability and forecast skill in NMME. J. Clim. 27(15) (2014)Google Scholar
- 8.Sloughter, J.M., Raftery, A.E., Gneitting, T., Fraley, C.: Probabilistic quantitative precipitation forecasting using Bayesian model averaging. Mon. Wea. Rev. 135 (2007)Google Scholar